Product Description
Marketing analysts use data mining techniques to gain a reliable understanding of customer buying habits and then use that information to develop new marketing campaigns and products. Visual mining tools introduce a world of possibilities to a much broader and non-technical audience to help them solve common business problems.
* Explains how to select the appropriate data sets for analysis, transform the data sets into usable formats, and verify that the sets are error-free
* Reviews how to choose the right model for the specific type of analysis project, how to analyze the model, and present the results for decision making
* Shows how to solve numerous business problems by applying various tools and techniques
* Companion Web site offers links to data visualization and visual data mining tools, and real-world success stories using visual data mining
 | US $53.33 End Date: Tuesday Jun-05-2012 6:58:10 PDT Buy It Now for only: US $53.33 Buy it now | Add to watch list |
In my opinion, there are two types of data
mining books.
The first type such as by Hand et’ al, Han,
Witten etc focus on the techniques.
The second type which this book falls into
focuses on how to apply the techniques.
I like this book more than other books
of the same type such as the one by
Herb Edelstein because it has a detailed
case study that is built upon throughout
the book.
This book is a good example of how to apply
data mining. It is obvious the authors have
done data mining in industry, otherwise they
wouldn’t have a section in the book on:
“Mapping Business Questions To Data Mining
Tasks”.
Highly recommended.
Amazon User Rating: 4 / 5
I believe Stephen Eick, Cheif Technology Officer of Visual Insights best put into words in the Advance Praise section of the book that “This book is a wonderful contribution and important resource for anyone building visual data mining systems. It combines down-to-earth, practical advice with thoughtful examples.”
In addition, Michael Berry of Data Miners, Inc states “As this book shows, visualization plays an important role in every step of the data mining process. Soukup and Davidson take the reader through every detail of this process, providing sample SQL code for each practical example. In fact, much of their advice on project planning and data extract, transformation and cleaning is applicable to all data mining projects, visual or not.”
I found the eight step VDM methodology applicable to data mining my own data. Highly recommended.
Amazon User Rating: 5 / 5
The examples are terrific, including those in color—and the business-oriented examples and cases are practical and detailed. The author also does a good job of covering tough areas, like verifying accuracy of visualizations, and selecting the correct data sets for analysis.
Amazon User Rating: 5 / 5
Most data mining books focus on the algorithms.
This book takes a different tack. It discusses
using the algorithms and visualization within a data mining
project. Alot of the book focuses on the “darker
side” of data mining: data preparation, model
performance and deploying your model once it is
built and tested. There are two chapters on
algorithms but they mainly focus on how to visualize
the model, its performance, expected vs actual
performance.
The book is well written and easy to follow. The
highly detailed retention case study is a nice addition.
One small critisim is that the authors get a little
to much on a soap box when discussing how to justify
to management a data mining project.
Amazon User Rating: 4 / 5
I’ve been doing data mining for years, but have only recently begun working with a visual tool (better left unnamed), that I found frustrating to use. This book has been really helpful in giving me the lay of the land on visual mining techniques and tools, and insight into the right kind of tool for the work I do. Thanks for helping me get on the right track!
Amazon User Rating: 5 / 5